Image semantic segmentation is intended to identify the image regions corresponding directly to objects in an image by labeling each pixel in the image to a semantic category. Contrary to the object recognition which merely detects the objects in the image, semantic segmentation assigns a category label to each pixel to indicate an object to which the pixel belongs. As such, semantic segmentation aims to assign a categorical label to every pixel in an image, which plays an important role in image analysis and self-driving systems.
Localization is a process of determining an exact location of a vehicle in an environment. Localization is important for navigating the vehicle within the environment. Localization is also important for avoiding obstacles in the environment. In some cases, localization can be more difficult when using semantic segmentation labeling because of varying extraneous objects appearing in the images upon which the semantic segmentation labeling was performed. Additionally, the accuracy of the image data and distance data from the sensor devices on an autonomous vehicle may be less than optimal. As such, there can be problems in generating an accurate vehicle position and velocity.